As AI continues to permeate various industries, the demand for skilled professionals in this field is rapidly increasing. India, with its robust technology sector, is emerging as a key player in this global AI revolution. However, the journey is not without its challenges, particularly in terms of equipping the workforce with the necessary AI skills.
Through in-depth discussions on ETCIO podcasts- The Sound of CIO and The SamurAI Code, leaders from NASSCOM, Meesho, and Flipkart share their insights on the essential skills required to thrive in this evolving AI landscape.
Pyramid approach
Debjani Ghosh, President, NASSCOM emphasizes a three-tiered approach to AI skills development, recognizing that AI will permeate various professions and industries.
“There are three levels which we cannot forget, because AI is going to be used by people. Everyone is going to use it—journalists, doctors, lawyers. When we think about AI skills as NASSCOM, we advocate a pyramid-level approach. Right on top, you have the skills that are needed for the few—the highest technical skills needed to build AI. This is where you have to create world-class data scientists and coders,” she says.
Ghosh continues to elaborate on the mid and foundational levels of the pyramid. “Then you have a mid-level, which is your entire white-collared population who are working in jobs like you and me, who will be using AI as a productivity tool. “
We have to know how to use AI safely to enhance our own productivity. We may not need to code, but we definitely have to know how to integrate it into our work in a safe manner.Debjani Ghosh, President, NASSCOM
The third layer is what we say for everyone, for all, which is where you have to know the basics of how to use AI in your day-to-day work. If you’re a farmer, it’s going to be on your phone—how do you use it to get the right information? So there are three levels of AI skills that we as NASSCOM advocate that the government should look at, not just building the top-level talent,” Ghosh adds.Ghosh underscores NASSCOM’s collaboration with the Ministry of Electronics and IT (MeitY) through the Future Skills program. “NASSCOM and MeitY’s Future Skills program focuses on building frontier tech skills and employability skills in both industry professionals and students. We are working with over 2000 colleges to ensure they have the right curriculum integrated, asking industry to create content because they know what is relevant. We are also working with the government to ensure that this curriculum gets credit under the New Credit Framework,” she says.
[Full podcast episode: Cracking AI’s Culture Code: Debjani Ghosh on investing in Indic language models]
Building competencies
Debdoot Mukherjee, Chief Data Scientist, Head of AI and Demand Engineering, Meesho, discusses the competencies required to build successful AI and machine learning teams, highlighting the importance of a well-rounded skill set. “If you look at a successful ML team, we tend to focus on three kinds of competencies: Knowledge of machine learning, statistics, deep learning; engineering skills to deploy these products at scale; and good product thinking and business thinking,” he adds.
Mukherjee outlines the specific roles within an AI team. “For the first competency—machine learning, statistics, deep learning—the people who go deep into that are called machine learning scientists or data scientists. Second, we have roles for ML engineers, software engineers in machine learning. The third competency involves partnering closely with product management and analysts to ensure we have the right mix to cover and check off all these competencies on every project.”
Mukherjee also emphasizes the importance of attracting top talent through challenging work.
The key thing that has worked for us in attracting talent is the quality of projects and opportunities available when they join the AI team at Meesho. We deliver this opportunity where you have a lot of freedom to pick up a problem, work on it, and really influence how millions of people in India shop.Debdoot Mukherjee, Chief Data Scientist, Head of AI and Demand Engineering, Meesho
[Full podcast episode: Building tailored AI technologies for Meesho users]
Critical competencies for data scientists
Mayur Datar, Chief Data Scientist, Flipkart sheds light on the specific competencies they look for when hiring data scientists. “We look at two or three core competencies of a data scientist. One is that they understand data science well—not just how to apply it, but understanding what goes under the hood. There’s a lot of mathematical underpinning to these algorithms. The second competency is the ability to take a business problem and convert that into a data science problem.
The third is being hands-on. Can you get your hands dirty with the data? Data is rarely of good quality—it always has missing values and irregular distributions. Do you have the right mindset to analyze the data, visualize it correctly, apply the right libraries, and build a solution?,” he adds.
Datar also highlights Flipkart’s emphasis on cultural fit and their core values. “Beyond technical competencies, we look for culture fitment—audacity, bias for action, and customer centricity. Audacity is about thinking big and solving for scale, ensuring that our solutions are accessible to the farthest corners of the nation,” he says.
[Full podcast episode: Flipkart’s Chief Data Scientist loads AI into cart for biz]
The insights from these industry leaders underline the diverse and multi-faceted approach required to build AI skills in India. Whether it’s through a pyramid approach, focusing on core competencies, or aligning with organizational values, the development of AI talent is crucial for staying competitive in the global market.
